A fundamental prerequisite for this is the correct determination of the biometric data of the eye required for the selection of an IOL.
According to the known state of the art, IOLs are selected or adapted on the basis of measured and/or estimated variables, wherein only individual parameters in the form of individual measured values or as an average value for defined patient groups are taken into consideration.
For one thing, the biometric data of the eye to be treated, determined by use of an ophthalmological measuring device, serve as input parameters for the calculation process; for another, the data of the (1 . . . n) IOLs that are possibilities for implantation serve for this purpose. These IOLs typically vary by IOL type (including variation of their asphericity or toricity) and IOL refractive power.
A wide-spread method for determining the refraction of the patient after insertion of the IOL is represented by what are called IOL formulas. Along with measured parameters, the IOL formulas are based on additional correction factors, on the basis of their simplified model assumptions. Depending on the IOL formula used, for example according to Holladay, Hoffer, Binkhorst, Colenbrander, Shammas or SRK, the approaches are correspondingly different.
In order to adapt the result of the calculation to the optimal refraction values that occur in a real case, correction factors determined empirically by way of a patient ensemble are used. However, this adaptation only ensures that the average value of the refraction values agrees with the formula for the test ensemble. Statistical errors that necessarily occur can typically be taken into consideration by the physician only on the basis of his/her experience, in that he/she corrects the calculated target refraction accordingly.
In order to minimize systematic errors in the calculation and selection of an IOL to be implanted in an eye, different approaches are selected at present, in accordance with the state of the art.
An alternative but not yet very wide-spread method is ray tracing. Ray tracing, as the term indicates (“ray”=ray and “to trace”=to trace), should be understood to be a method for ray tracing.
It is known that we perceive objects in our surroundings only because they are irradiated by a light source and they reflect these light rays, part of which rays finally reach our eyes. The ray tracing method simulates this elementary natural phenomenon. If the optical system, i.e. the individual human eye, is known with all of its optical elements, then a “real” image that occurs on the retina can be calculated by means application of ray tracing. The method is therefore based on a detailed eye model, using the cornea topography of the eye.
It is true that in this method, no general correction factors are used, but certain assumptions are required as far as the effective (post-operative) lens position (ELP) is concerned. This method is suitable for eyes having the most varied biometric parameters, such as, for example: long, normal, short, post-LASIK, etc.
Using ray tracing, the IOL refractive value and the residual refraction are then calculated. In order to achieve a good correlation with the subjective visual acuity, i.e. a result comparable with the perception of the patient, different selection criteria or metrics can be used for the calculation. Although retinal image metrics have proven to be particularly suitable in this regard, other optical evaluation parameters or selection criteria known to a person skilled in the art can also be used.
While a comparison between the use of ray tracing methods and IOL formulas is undertaken by P.-R. Preussner et al. in [1], they deal with a calculation model for ray tracing in [2]. Based on the individual measured values and the estimated variables, an eye model is developed here. The imaging quality at the retina/fovea is determined as an evaluation value here.
Because of the complexity of the entire process of cataract surgery, use of the method of ray tracing alone for calculating the IOL is not sufficient to guarantee that the result of the calculation of the post-operative refraction is better than with the formula approaches.
The most important prerequisite for successful ray tracing is precise and reproducible collection and analysis of the pre-operative measured data. Data collection determines the limits as to how complex an eye model that serves as the basis for the calculation can be. Prediction of the effective or real post-operative position and location of the implanted IOL is a further factor that is just as decisive as the surgical procedure and the subsequent healing process itself.
Numerous measuring methods for precise and reproducible collection and analysis of the pre-operative measured data are known from the state of the art; these vary with regard to the parameter to be measured, because no universal measuring method exists.
For example, numerous measuring techniques based on reflection, such as keratometers, Placido and other topographs, Scheimpflug cameras and slit lamps exist for measuring the cornea curvature, particularly its anterior surface and thickness, as do measuring techniques that are based on optical coherence tomography. Each of these technologies has advantages and disadvantages.
For example, it is true that very robust and reproducible measurements, but only a very simple model of the cornea can be implemented using distance-independent, telecentric keratometers. In contrast to this, topographs with a Placido disk offer detailed information about the cornea surface, but the reproducibility of the measured values is not comparable with telecentric keratometry.
Because Scheimpflug-based and OCT-based devices do not measure the entire region of interest at the same time, they are therefore affected by movement artifacts of the eye. However, they have the advantage, as compared with keratometers and Placido-based topographs, of allowing measurements of the posterior cornea surface, as well.
Something similar holds true for the determination of other biometric parameters of the eye required for calculating and selecting an IOL, such as anterior chamber depth, lens thickness, and eye length. The eye models known in the state of the art, such as those of Gauss, Liu-Brennan, and others, for example, are generally based on schematic models. It is true that in this regard, specific parameters can be replaced with individual measured data of patients, but theoretical definitions, reference points or axes generally remain fixed as the basis of schematic models.
In the end result, reference points or axes of the schematic eye models frequently do not coincide with the reference points or axes of the biometric data from the measuring devices.
As has already been mentioned, prediction of the post-operative position and location of the implanted IOL is also a decisive factor. Formula approaches for statistical optimization, for example, are known for prediction. In this regard, all the variables that influence the refractive results post-operatively are taken into consideration for determining the effective lens position. Such formula approaches are only possible with reference to the average population.
A method for calculating an intraocular lens to be implanted, in which method the results of numerous cataract operations are used in order to automatically optimize the calculation of intraocular lenses to be implanted in the future, is described in WO 2013/037946 A1. For this purpose, a post-operative determination of biometric data as well as of the objective, wave-front-based residual refraction takes place. The measured values determined pre-operatively and post-operatively are used for optimization of the surgically induced astigmatism and of the anatomical, post-operative lens position, and are included in the calculation of future IOLs to be implanted. In order for the proposed method to produce a noticeable effect, a correspondingly great number of data of post-operative measurements is required.
DE 10 2011 106 714 A1 describes a method for optimized prediction of the post-operative, anatomical position of an implanted intraocular lens, in that the post-operative lens position is predicted on the basis of known measured values, such as the cornea thickness, the anterior chamber depth, the eye length, as well as the distances of the capsular sac equator or of the lens haptic from the anterior lens surface. In this regard, the location of the intraocular lens to be implanted is included in the calculation, along with the anatomical, post-operative position of the lens, and additional parameters of the pseudophakic eye, which parameters have not yet been taken into consideration, are used for this purpose. The method is based on the use of suitable calculation methods, biometric formulas or ray tracing.
Other methods can provide a more direct prediction in that the IOL position is estimated on the basis of the individual biometric data. See U.S. Pat. No. 5,968,095 A in this regard.
In the solution described in DE 10 2011 103 224 A1, a precise prediction of the post-operative location of the IOL is supposed to be achieved in that along with an IOL, operation parameters within the scope of the IOL implantation are also selected. In this regard, corresponding starting parameters are determined from predetermined, estimated or measured input parameters, in that at least two input parameters are varied with one another, at least one input parameter of which is present as a distribution function. The resulting distribution function(s) is/are optimized using corresponding target defaults and used as a decision aid.
However, on the basis of the limited complexity of eye models and of the general lack of information concerning design characteristics of IOLs, an even more precise prediction of the post-operative position and location of an implanted IOL is not possible.
For this purpose, additional statistical correction factors both with regard to the IOL design and with regard to the average population would necessarily be required.
A problem in the selection of the IOL to be implanted can be seen in that the selection takes place merely using the data calculated from the optical parameters, and the subjective aspect of seeing, i.e. the subjective vision performance is not taken into consideration.
In this regard, the complete optical and psycho-physical experiences with regard to the vision process of a patient should be understood to be the subjective vision performance, in which the light that strikes the retina by after transmission by the optical components of the eye is detected by the photoreceptors, and signal from the photoreceptors are processed, and transmitted to the visual cortex in the brain, where visual perception actually takes place.
A difficulty in cataract surgery now exists in that the subjective vision performance of a patient can only be measured after the operation, when it is already too late for corrections.
For this reason, subjective experiences of the patients relating to post-operative refraction must be statistically collected, in order to be able to use these in the selection of the IOL to be implanted.
Since the measurement principles known according to the state of the art are only suitable for determining the optical parameters of an eye, estimation of the subjective visual performance is very limited. A first step for taking into consideration the subjective visual performance can be seen in calculation of the retinal image field metrics, in which the contrast and the phase transfer function of an object are calculated by means of the optical components of the eye in the image plane of the retina, based on an individual optical aberrations. In addition, some psycho-physical aspects of human vision can be taken into consideration by means of calculating the contrast transfer function.
Calculation of the retinal image metrics of a higher and/or lower order are equally practical not only for spherical and aspheric IOL designs but also for toric and multi-focal IOL designs, in order to facilitate the determination of the target refraction by means of simulation of the complex interactions between IOL and eye.
In the following, individual solutions will be discussed, with which the process of measuring, calculating, and selecting the IOL to be implanted is supposed to be improved.
In DE 10 2011 103 223 A1, a method for pre-operative selection of an intraocular lens to be implanted in an eye is described. IOLs that appear suitable are selected on the basis of an individual eye model, using their optical parameters, and the residual refraction is calculated by means of ray tracing for the IOLs that appear suitable. The decision regarding selection of an IOL is facilitated for the physician in that it is possible to compare IOLs that appear suitable with one another, and to take special requirements, criteria or parameters into consideration when making the selection.
The patent application DE 10 2012 019 473.0, not yet published, proposes a method for reliable determination of the axis length of an eye, in which method the axis length of an eye is determined by means of optical coherence tomography (OCT). In this regard, the alignment of the measuring device relative to the eye is monitored for all one-dimensional and two-dimensional scans, in order to be able to guarantee a reliable determination of the axis length of the eye. For this purpose, the retinal tissue structure detected from the B scans is segmented using one or different criteria, the fovea is detected, and its lateral distance from the optical axis of the measuring device is determined.
The patent application DE 10 2012 019 474.9, also not yet published, describes an apparatus for reliable determination of biometric measurement variables of the entire eye, as they are required for calculating IOLs by formulas or ray tracing. For this purpose, the surfaces of the entire eye that are optically relevant for the visual capacity of the eye are determined in terms of their location and their profile in the eye. The measurement arrangement used for this purpose consists of a multi-point keratometer and an OCT arrangement, wherein telemetric illumination and telecentric detection take place by means of the multi-point keratometer, and the OCT arrangement is designed as a laterally scanning swept-source system.
A method for imaging systems with which eye movements are monitored and compensated is described in U.S. Pat. No. 7,452,077 B2. In this regard, the likeness of an image projected into the eye is used to detect the current eye position. Tracking of eye movements allows precise registration of image data for the scan sites and thereby improved imaging. In order to be able to register a recorded pachymetry card precisely, the cornea vertex (vertex) must be recorded. The relationship between the highest point of the cornea arch in every B scan and the vertex is used to adjust the image, to indicate decentering correctly, and to correct errors in the pachymetry card.
In WO 2012/062453 A1, a method for model-based determination of the biometrics of eyes is described. The method for determining multiple lengths and other variables using localized boundary surfaces is based on optical coherence tomography. For this purpose, different scans are implemented with different scan patterns and focus settings, in order to adapt a parametric eye model accordingly. The biometric measured values can be derived from this adapted eye model. It is absolutely necessary, in this regard, that the scans that are implemented contain at least two of the boundary surfaces of the eye, in each instance.
All of the known solutions have the disadvantage that although they improve individual aspects of the process of measuring, calculating, and selecting the IOL to be implanted, considered in and of themselves they cannot, however, produce any qualitative jump in the determination of the target refraction and the selection of the intraocular lens to be implanted in an eye.
WO 2010/035139 A2 describes a solution for configuring and implanting a customized intraocular lens, in which the eye of a patient is analyzed and its biometric data are recorded. The system also comprises a modeling module and an optimization module, in order to produce an optimized IOL model, as well as a module for producing the customized IOL based on the IOL model. The goal of the solution proposed here can be seen in creating the IOL that best meets the requirements of the patient, using the biometric measured values and special specifications of the surgeon. This has the disadvantage that the psycho-physical experiences with regard to the vision process of a patient, in particular, are not taken into consideration.